import torch

teacher_ft_path = '../../logs/ag_ft/baseline_new_orien/model_16500.pt'
student_loco_path = '../../logs/ag_ft/student_model/model_12000.pt'
combined_path = '../../logs/ag_ft/combined_model/model_bbaseline_new_orien_16500_com_12000.pt'

teacher_dict = torch.load(teacher_ft_path)
student_dict = torch.load(student_loco_path)

combined_dict = {
            'model_state_dict': teacher_dict['model_state_dict'],
            'estimator_state_dict': teacher_dict['estimator_state_dict'],
            'optimizer_state_dict': teacher_dict['optimizer_state_dict'],
            'depth_encoder_state_dict': student_dict['depth_encoder_state_dict'],
            'depth_actor_state_dict': student_dict['depth_actor_state_dict'],
            'iter': 0,
            'infos': None,
            }

torch.save(combined_dict, combined_path)
